Creation of topic map by identifying topic chain in chinese

XML Topic maps enable multiple, concurrent views of sets of information objects and can be used to different applications. For example, thesaurus-like interfaces to corpora, navigational tools for cross-references or citation systems, information filtering or delivering depending on user profiles, etc. However, to enrich the information of a topic map or to connect with some document's URI is very labor-intensive and time-consuming. To solve this problem, we propose an approach based on natural language processing techniques to identify and extract useful information in raw Chinese text. Unlike most traditional approaches to parsing sentences based on the integration of complex linguistic information and domain knowledge, we work on the output of a part-of-speech tagger and use shallow parsing instead of complex parsing to identify the topics of sentences. The key elements of the centering model of local discourse coherence are employed to extract structures of discourse segments...

• Type: Conference
• Year: 2004
• Where: DOCENG
• Authors: Ching-Long Yeh, Yi-Chun Chen
• Keywords: DOCENG 2004, Natural Language Processing, Topic Maps, XML Topic Maps